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Buried in the middle of nowhere

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Driving out of Death Valley last week, on a lonely road miles from the nearest car or human-built structure, I came upon a striking grave marker. I was compelled to pull over and check it out, and what I found was like history smacking me in the face. Isolated but well-tended, the grave was on a ridge overlooking the Eastern Sierras in the faraway distance. A weathered, hand-carved board read:
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It had to be a pioneer family, I thought. How tragic to make it so far west just to die there on the trail. More fascinating still, scattered around the grave, atop a muddy blanket, were trinkets left for the children: a decomposing ragdoll, some coins, a few bleached crayons and even a half-eaten package of M&Ms (how thoughtful).
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But who were these unfortunate kids? Miles from wi-fi, I had to wait until I got home to find out. A little Googling found the website of David KcKillips, a cousin four times removed from the infant pioneers, who tells the story (after the jump):

"In the 1870s, the McKellips ran a way station near the current gravesite. Managing a way station was usually a family affair. The wife of the manager would prepare food and lodgings, while the manager would tend to the animals and any repairs to the stages and wagons. The children would help whichever of their parents they could. In January of 1874 a dreadful sickness came into the valley [Diphtheria, we think] and entire families took ill at the same time. There was none left well to care for the sick. Larkin & Lorenza McKellips died and of necessity had been buried very close to the house. After the family had gotten well, they must have carefully tended the little grave sites. The father had the dreadful chore of carving their names and dates into a grave marker. When the time came for the family to leave the area, the way station was no longer needed, the mother's heart must have been heavy with anguish.

For over half a century the graves laid forgotten. In 1947, Bill James, who leased the "White Swan" talc mine was wandering over the desert and found two grave markers. It was impossible to discern what was originally carved into the worn and weathered wooden boards. The mystery intrigued Mr. James and by inquiring with all of the old-timers in the area he was gradually able to piece together the story of the children and their untimely deaths. Mr. James carved new markers and the James family and the Wallace Campbell family of Darwin maintained the graves until the road department crew took over."

These days, the California Dept. of Transportation is responsible for maintaining the grave. When the road was set to be straightened in the 1980s, they re-engineered it to go around the site. It stands as a fascinating piece of history, sans interpretive signs, ropes or tour guides; the best kind.

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iStock // Ekaterina Minaeva
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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
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iStock // Ekaterina Minaeva

Jacques Mattheij made a small, but awesome, mistake. He went on eBay one evening and bid on a bunch of bulk LEGO brick auctions, then went to sleep. Upon waking, he discovered that he was the high bidder on many, and was now the proud owner of two tons of LEGO bricks. (This is about 4400 pounds.) He wrote, "[L]esson 1: if you win almost all bids you are bidding too high."

Mattheij had noticed that bulk, unsorted bricks sell for something like €10/kilogram, whereas sets are roughly €40/kg and rare parts go for up to €100/kg. Much of the value of the bricks is in their sorting. If he could reduce the entropy of these bins of unsorted bricks, he could make a tidy profit. While many people do this work by hand, the problem is enormous—just the kind of challenge for a computer. Mattheij writes:

There are 38000+ shapes and there are 100+ possible shades of color (you can roughly tell how old someone is by asking them what lego colors they remember from their youth).

In the following months, Mattheij built a proof-of-concept sorting system using, of course, LEGO. He broke the problem down into a series of sub-problems (including "feeding LEGO reliably from a hopper is surprisingly hard," one of those facts of nature that will stymie even the best system design). After tinkering with the prototype at length, he expanded the system to a surprisingly complex system of conveyer belts (powered by a home treadmill), various pieces of cabinetry, and "copious quantities of crazy glue."

Here's a video showing the current system running at low speed:

The key part of the system was running the bricks past a camera paired with a computer running a neural net-based image classifier. That allows the computer (when sufficiently trained on brick images) to recognize bricks and thus categorize them by color, shape, or other parameters. Remember that as bricks pass by, they can be in any orientation, can be dirty, can even be stuck to other pieces. So having a flexible software system is key to recognizing—in a fraction of a second—what a given brick is, in order to sort it out. When a match is found, a jet of compressed air pops the piece off the conveyer belt and into a waiting bin.

After much experimentation, Mattheij rewrote the software (several times in fact) to accomplish a variety of basic tasks. At its core, the system takes images from a webcam and feeds them to a neural network to do the classification. Of course, the neural net needs to be "trained" by showing it lots of images, and telling it what those images represent. Mattheij's breakthrough was allowing the machine to effectively train itself, with guidance: Running pieces through allows the system to take its own photos, make a guess, and build on that guess. As long as Mattheij corrects the incorrect guesses, he ends up with a decent (and self-reinforcing) corpus of training data. As the machine continues running, it can rack up more training, allowing it to recognize a broad variety of pieces on the fly.

Here's another video, focusing on how the pieces move on conveyer belts (running at slow speed so puny humans can follow). You can also see the air jets in action:

In an email interview, Mattheij told Mental Floss that the system currently sorts LEGO bricks into more than 50 categories. It can also be run in a color-sorting mode to bin the parts across 12 color groups. (Thus at present you'd likely do a two-pass sort on the bricks: once for shape, then a separate pass for color.) He continues to refine the system, with a focus on making its recognition abilities faster. At some point down the line, he plans to make the software portion open source. You're on your own as far as building conveyer belts, bins, and so forth.

Check out Mattheij's writeup in two parts for more information. It starts with an overview of the story, followed up with a deep dive on the software. He's also tweeting about the project (among other things). And if you look around a bit, you'll find bulk LEGO brick auctions online—it's definitely a thing!

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Nick Briggs/Comic Relief
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What Happened to Jamie and Aurelia From Love Actually?
May 26, 2017
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Nick Briggs/Comic Relief

Fans of the romantic-comedy Love Actually recently got a bonus reunion in the form of Red Nose Day Actually, a short charity special that gave audiences a peek at where their favorite characters ended up almost 15 years later.

One of the most improbable pairings from the original film was between Jamie (Colin Firth) and Aurelia (Lúcia Moniz), who fell in love despite almost no shared vocabulary. Jamie is English, and Aurelia is Portuguese, and they know just enough of each other’s native tongues for Jamie to propose and Aurelia to accept.

A decade and a half on, they have both improved their knowledge of each other’s languages—if not perfectly, in Jamie’s case. But apparently, their love is much stronger than his grasp on Portuguese grammar, because they’ve got three bilingual kids and another on the way. (And still enjoy having important romantic moments in the car.)

In 2015, Love Actually script editor Emma Freud revealed via Twitter what happened between Karen and Harry (Emma Thompson and Alan Rickman, who passed away last year). Most of the other couples get happy endings in the short—even if Hugh Grant's character hasn't gotten any better at dancing.

[h/t TV Guide]

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